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The investment model in preventive maintenance in multi-level production systems

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  • Lee, Hsu-Hua

Abstract

In this research, cost/benefit models for investments made in quality improvements are developed to measure the impact of quality programs and to predict the return of an investment in these programs in a multi-level assembly system. Using these models, the decision makers can decide whether and how much to invest in quality improvement projects. The relationship between the investment and return on investment can be developed based on the tangible variables. The investment model in preventive maintenance is developed in a multi-level assembly system. The investment in preventive maintenance is to reduce the variance and the deviation of the mean from the target value of the quality characteristic, and hence to reduce the proportion of defectives and also to increase reliability. The proportion of defectives can be linked to manufacturing cost, inventory cost, and profit loss. The reliability is linked to warranty cost. The total costs in this investment model include manufacturing cost, setup cost, holding cost, profit loss, and warranty cost.

Suggested Citation

  • Lee, Hsu-Hua, 2008. "The investment model in preventive maintenance in multi-level production systems," International Journal of Production Economics, Elsevier, vol. 112(2), pages 816-828, April.
    • Handle: RePEc:eee:proeco:v:112:y:2008:i:2:p:816-828
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    References listed on IDEAS

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    Cited by:

    1. Shafiee, Mahmood & Chukova, Stefanka, 2013. "Maintenance models in warranty: A literature review," European Journal of Operational Research, Elsevier, vol. 229(3), pages 561-572.
    2. Mehran Ullah & Biswajit Sarkar & Iqra Asghar, 2019. "Effects of Preservation Technology Investment on Waste Generation in a Two-Echelon Supply Chain Model," Mathematics, MDPI, vol. 7(2), pages 1-20, February.
    3. Rung-Hung Su & Ming-Wei Weng & Yung-Fu Huang, 2020. "Innovative maintenance problem in a two-stage production-inventory system with imperfect processes," Annals of Operations Research, Springer, vol. 287(1), pages 379-401, April.
    4. Guowei Liu & Jianxiong Zhang & Wansheng Tang, 2015. "Joint dynamic pricing and investment strategy for perishable foods with price-quality dependent demand," Annals of Operations Research, Springer, vol. 226(1), pages 397-416, March.
    5. Rivera-Gómez, Héctor & Gharbi, Ali & Kenné, Jean-Pierre & Montaño-Arango, Oscar & Hernández-Gress, Eva Selene, 2018. "Subcontracting strategies with production and maintenance policies for a manufacturing system subject to progressive deterioration," International Journal of Production Economics, Elsevier, vol. 200(C), pages 103-118.
    6. Hsu, P.H. & Wee, H.M. & Teng, H.M., 2010. "Preservation technology investment for deteriorating inventory," International Journal of Production Economics, Elsevier, vol. 124(2), pages 388-394, April.
    7. Ludvík Friebel & Jana Friebelová, 2012. "Stochastic analysis of maintenance process costs in the IT industry: a case study," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 20(3), pages 393-408, September.
    8. Sana, Shib Sankar, 2010. "An economic production lot size model in an imperfect production system," European Journal of Operational Research, Elsevier, vol. 201(1), pages 158-170, February.
    9. Nourelfath, Mustapha, 2011. "Service level robustness in stochastic production planning under random machine breakdowns," European Journal of Operational Research, Elsevier, vol. 212(1), pages 81-88, July.

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